Angela Lemke

CXM: A New Tool for Mapping Breast Cancer Risk in the Tumor Microenvironment

The majority of causative variants in familial breast cancer remain unknown. Of the known risk variants, most are tumor cell autonomous, and little attention has been paid yet to germline variants that may affect the tumor microenvironment. In this study, we developed a system called the Consomic Xenograft Model (CXM) to map germline variants that affect only the tumor microenvironment. In CXM, human breast cancer cells are orthotopically implanted into immunodeficient consomic strains and tumor metrics are quantified (e.g., growth, vasculogenesis, and metastasis). Because the strain backgrounds vary, whereas the malignant tumor cells do not, any observed changes in tumor progression are due to genetic differences in the nonmalignant microenvironment. Using CXM, we defined genetic variants on rat chromosome 3 that reduced relative tumor growth and hematogenous metastasis in the SS.BN3(IL2Rγ) consomic model compared with the SS(IL2Rγ) parental strain. Paradoxically, these effects occurred despite an increase in the density of tumor-associated blood vessels. In contrast, lymphatic vasculature and lymphogenous metastasis were unaffected by the SS.BN3(IL2Rγ) background. Through comparative mapping and whole-genome sequence analysis, we narrowed candidate variants on rat chromosome 3 to six genes with a priority for future analysis. Collectively, our results establish the utility of CXM to localize genetic variants affecting the tumor microenvironment that underlie differences in breast cancer risk.

SH2B3 Is a Genetic Determinant of Cardiac Inflammation and Fibrosis

Background—Genome-wide association studies are powerful tools for nominating pathogenic variants, but offer little insight as to how candidate genes affect disease outcome. Such is the case for SH2B adaptor protein 3 (SH2B3), which is a negative regulator of multiple cytokine signaling pathways and is associated with increased risk of myocardial infarction (MI), but its role in post-MI inflammation and fibrosis is completely unknown. Methods and Results—Using an experimental model of MI (left anterior descending artery occlusion/reperfusion injury) in wild-type and Sh2b3 knockout rats (Sh2b3em2Mcwi), we assessed the role of Sh2b3 in post-MI fibrosis, leukocyte infiltration, angiogenesis, left ventricle contractility, and inflammatory gene expression. Compared with wild-type, Sh2b3em2Mcwi rats had significantly increased fibrosis (2.2-fold; P<0.05) and elevated leukocyte infiltration (>2-fold; P<0.05), which coincided with decreased left ventricle fractional shortening (−&Dgr;11%; P<0.05) at 7 days post left anterior descending artery occlusion/reperfusion injury. Despite an increased angiogenic potential in Sh2b3em2Mcwi rats (1.7-fold; P<0.05), we observed no significant differences in left ventricle capillary density between wild-type and Sh2b3em2Mcwi rats. In total, 12 genes were significantly elevated in the post left anterior descending artery occluded/reperfused hearts of Sh2b3em2Mcwi rats relative to wild-type, of which 3 (NLRP12, CCR2, and IFN&ggr;) were significantly elevated in the left ventricle of heart failure patients carrying the MI-associated rs3184504 [T] SH2B3 risk allele. Conclusions—These data demonstrate for the first time that SH2B3 is a crucial mediator of post-MI inflammation and fibrosis.

mTORC1 and mTORC2 differentially promote natural killer cell development

Natural killer (NK) cells are innate lymphoid cells that are essential for innate and adaptive immunity. Mechanistic target of rapamycin (mTOR) is critical for NK cell development; however, the independent roles of mTORC1 or mTORC2 in regulating this process remain unknown. Ncr1iCre-mediated deletion of Rptor or Rictor in mice results in altered homeostatic NK cellularity and impaired development at distinct stages. The transition from the CD27+CD11b− to the CD27+CD11b+ stage is impaired in Rptor cKO mice, while, the terminal maturation from the CD27+CD11b+ to the CD27−CD11b+ stage is compromised in Rictor cKO mice. Mechanistically, Raptor-deficiency renders substantial alteration of the gene expression profile including transcription factors governing early NK cell development. Comparatively, loss of Rictor causes more restricted transcriptome changes. The reduced expression of T-bet correlates with the terminal maturation defects and results from impaired mTORC2-AktS473-FoxO1 signaling. Collectively, our results reveal the divergent roles of mTORC1 and mTORC2 in NK cell development.

Abstract 408: Evidence of DLL4, NNAT, and SLC35C2 in suppression of breast cancer initiation, growth, and metastasis

Breast cancer affects 1 in 8 women, resulting in 40,000 deaths annually. In most cases, a single cause of breast cancer cannot be found, but rather multiple environmental and genetic factors contribute to overall disease susceptibility. This, combined with complex gene interaction in both malignant tumor cells and nonmalignant tumor microenvironment (TME) cells, poses significant challenges in sifting through the many variants that contribute to the ~31% of breast cancer risk that is heritable. Here, we narrowed the regions associated with breast cancer risk on rat chromosome 3 (RNO3) by introgressing portions of RNO3 derived from the BN rat (protective strain) onto the genomic background of the SS rat (susceptible strain). These SS.BN3 congenics were then phenotyped for DMBA-induced mammary tumor incidence, latency, and multiplicity, which revealed two loci in close proximity that contribute to mammary tumor risk: chr3:95-130Mb (QTL1) and chr3: 154-177Mb (QTL2). By comparing these data with a previous study (Flister et al. Breast Cancer Res Treat. 2017 Aug;165(1):53-64.), we concluded that QTL1 is dependent on the host TME, whereas QTL2 directly modifies breast tumorigenesis and cancer cell proliferation. By combining the congenic mapping studies with genomic and transcriptomic sequencing, and functional analysis, we have now localized the top three candidate modifiers on RNO3: DLL4 (QTL1; TME modifier), NNAT (QTL2; cancer cell modifier), and SLC35C2 (QTL2; cancer cell modifier). Collectively, these data demonstrate the effects of several novel breast cancer modifiers, as well as highlight the potential interactions between modifiers of the malignant cancer cells and the nonmalignant host TME. Citation Format: Cody Plasterer, Angela Lemke, Dana Murphy, Carmen Bergom, Amit Joshi, Hallgeir Rui, Michael J. Flister. Evidence of DLL4, NNAT, and SLC35C2 in suppression of breast cancer initiation, growth, and metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 408.

Abstract B07: Utilizing consomic xenograft models to identify genetic variants in the tumor microenvironment that determine breast cancer radiation responses

Progress in elucidating the molecular basis of breast cancer has allowed for treatment breakthroughs such as anti-estrogen and Her2-targeted therapy. It has also shaped the approaches to both surgical and systemic therapy. However, no similar use of molecular information has been utilized to better direct the use of radiation therapy. The development of predictive tools for the radiosensitivity of tumors could allow for personally tailored radiation doses, with treatment de-escalation for radiosensitive tumors, or dose escalation or the use of adjunct treatments in the case of radioresistant tumors. Communication between malignant tumor cells and the tumor microenvironment (TME) underlies most aspects of tumor biology, including chemotherapy and radiation resistance. We have developed a Consomic Xenograft Model (CXM), which maps germline variants that impact only the TME, as well as a species-specific RNA-seq (SSRS) protocol which allows detection of expression changes in the malignant and nonmalignant cellular compartments of tumor xenografts, in parallel and without cell-sorting. Here we utilize these unique techniques to identify genetic variants in the TME that can affect radiation sensitivity. In CXM, human triple negative breast cancer MDA-MD-231 cells are orthotopically implanted into immunodeficient (IL2Rγ-/-) consomic rat strains, which are rat strains in which an entire chromosome is introgressed into the isogenic background of another inbred strain by selective breeding. Because the strain backgrounds are different but the tumor cells are not varied, the observed changes in tumor progression are due to genetic differences in the non-malignant TME. We hypothesized that the tumors in SS.BN3 rats (identical to SS rats but with BN strain chromosome 3) would be more sensitive to radiation due to increased tumor vascularity via CD31 staining, and increased tumor blood volume capacity, as measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Our studies demonstrate differential responses to radiation in the CXM model comparing parental SS (IL2Rγ) rats to SS.BN3 (IL2Rγ) rats treated with fractionated radiation therapy (4 Gray x 3), with altered tumor growth kinetics and tumor recurrence rates. A difference was seen in time to 5-fold increase in tumor growth, with 44 vs. >130 days for SS versus SS.BN3 rats (supra-additive, p 130 days) in the SS versus SS.BN3 rats (p=0.02). These results suggest that genetic determinants in the TME affect the radiation sensitivity of genetically identical tumor cells. Using SSRS, we identified a number of candidates on rat chromosome 3 that may potentially influence radiation sensitivity by altering the tumor vasculature. Future studies will further dissect the pathways responsible for the changes in radiation sensitivity. Determining TME factors that affect the radiation sensitivity of tumors has the potential to allow for more tailored and effective radiation treatments in breast cancer. Citation Format: Carmen Bergom, Michael Straza, Amy Rymaszewski, Anne Frei, Angela Lemke, Shirng-Wern Tsaih, Howard Jacob, Michael J. Flister. Utilizing consomic xenograft models to identify genetic variants in the tumor microenvironment that determine breast cancer radiation responses. [abstract]. In: Proceedings of the AACR Special Conference: Function of Tumor Microenvironment in Cancer Progression; 2016 Jan 7–10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2016;76(15 Suppl):Abstract nr B07.

Abstract PR08: New tools for mapping genetic modifiers of cancer risk in the tumor microenvironment

The majority of heritable breast cancer risk is unknown. One potential source of “missing heritability” is genetic modifiers in the tumor microenvironment (TME). Although genetic modifiers in the TME have long been suspected, they have rarely been studied and are largely unknown. Here, we used two new techniques: the Consomic Xenograft Model (CXM) and species-specific RNA-seq (SSRS) to map genetic modifiers in the TME. In CXM, human breast cancer xenografts are implanted in immunodeficient consomic rat strains and tracked for tumor progression. Because the rat strains vary by one chromosome (i.e., consomic), whereas the malignant tumor cells do not differ, any observed changes in tumor phenotypes are due to genetic modifiers in the TME and can be localized to one chromosome. The SSRS method uses probabilistic mapping of RNAseq reads to a joint human and rat transcriptome to assess differential expression (DE) in malignant (human) tumor cells and the nonmalignant (rat) TME. Validation of SSRS revealed >99.4% specificity in calling human or rat reads, which was significantly better than conventional RNA-seq. Using CXM, we found that BN-derived genetic variant(s) on rat chromosome 3 significantly reduced growth of MDA-MB-231-Luc (231Luc+) tumors by 49% (P 4-fold; P Citation Format: Michael J. Flister, Alexander Stoddard, Shirng-Wern Tsaih, Angela Lemke, Jozef Lazar, Howard Jacob. New tools for mapping genetic modifiers of cancer risk in the tumor microenvironment. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr PR08.

Abstract 3217: NextGen strategies for mapping genetic modifiers in the tumor microenvironment

Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA The majority of heritable breast cancer risk is unknown. One potential source of “missing heritability” is genetic modifiers in the tumor microenvironment (TME). Although genetic modifiers in the TME have long been suspected, they have rarely been studied and are largely unknown. Here, we used two new techniques: the Consomic Xenograft Model (CXM) and species-specific RNA-seq (SSRS) to map genetic modifiers in the TME. In CXM, human breast cancer xenografts are implanted in immunodeficient consomic rat strains and tracked for tumor progression. Because the rat strains vary by one chromosome (i.e., consomic), whereas the malignant tumor cells do not differ, any observed changes in tumor phenotypes are due to genetic modifiers in the TME and can be localized to one chromosome. The SSRS method uses probabilistic mapping of RNAseq reads to a joint human and rat transcriptome to assess differential expression (DE) in malignant (human) tumor cells and the nonmalignant (rat) TME. Validation of SSRS revealed >99.4% specificity in calling human or rat reads, which was significantly better than conventional RNA-seq. Using CXM, we found that BN-derived genetic variant(s) on rat chromosome 3 significantly reduced growth of MDA-MB-231-Luc (231Luc+) tumors by 49% (P 4-fold; P<0.001) than any other rat chromosome. Moreover, a two-sample Kolmogorov-Smirnov test revealed that the difference in distributions of adjusted p-values for RN03 versus the rest of the genome was highly significantly higher for DE genes (P = 3.152e-08) or DE transcripts (P = 3.441e-16). Compared with other rat chromosomes, RNO3 also had by far the highest incidence of alternative isoform usage (91% of all instances). Pathway analysis of DE genes using DAVID revealed that the two most significant GO clusters were extracellular matrix (49 genes; P<10−20) and blood vessel development (43 genes; P<10−17), which recapitulated the vascular defects observed in the SS.BN3IL2Rγ tumors. Collectively, our data demonstrate that CXM and SSRS can be used to detect genetic modifiers in the TME. Citation Format: Michael Flister, Angela Lemke, Michael Dwinell, Carmen Bergom, James Shull, Howard Jacob. NextGen strategies for mapping genetic modifiers in the tumor microenvironment. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3217. doi:10.1158/1538-7445.AM2015-3217